Decision support for energy performance and incremental investment in high-rise hotel envelope design using surrogate-assisted Pareto optimization

Early-stage high-rise hotel envelope design requires balancing operational energy performance with additional initial investment, but multi-objective optimization results are often difficult to use directly for comparing design alternatives. This study develops a surrogate-assisted energy–investment decision-support workflow for comparing high-rise hotel envelope design alternatives in Guangzhou’s hot-summer and warm-winter climate. Prototypical hotel models were derived from 78 engineering drawings and used to generate EnergyPlus-based parametric simulation datasets. Sensitivity analysis was conducted to identify influential geometric, internal-load, and thermophysical variables, and a surrogate energy prediction model was developed for efficient energy-evaluation. The surrogate model was then coupled with an incremental investment function to generate EUI–investment Pareto fronts using NSGA-II. Knee-point identification, and budget-constrained screening, were applied to identify representative and budget-feasible envelope design alternatives. The selected surrogate model showed acceptable agreement for early-stage comparison, with absolute deviations of 2.38%–8.11% across six prototypical models and 5.59%–11.25% in two real-project geometry checks. The Pareto fronts revealed nonlinear EUI–investment trade-offs, while the knee-point solutions indicated plan-type-specific priorities in window solar-control performance, roof insulation, and surface solar absorptance. A case-based demonstration using real project geometric inputs tested the procedural applicability of the workflow beyond the prototypical models. The proposed workflow enables performance-informed energy–investment decision-making and identifies interpretable, budget-feasible envelope design alternatives for high-rise hotels at the early design stage.